Inspiration
While brainstorming for this hackathon, a member of our team made a remark about how much food is wasted at our university dinning hall. This conversation continued, and we discussed that restaurants, grocery stores and other food outlets have a similar problem. Another member of the team commented that when they used to work a restaurant, the restaurant had perfectly safe, clean, and edible food at the end of the day, but the owners did not know what outlets existed for donating the extra food to people in need. There are millions of food insecure people in need, and extra food available that is being thrown away. Our team feels awful about the global food waste problem exists, and this inspired us to create a solution in order to fix this injustice.
What it does
Our app connects restaurants, schools, hotels, hospitals, and grocery stores with food banks in order to solve the global battle against food waste, help the environment, and provide access to food to those who need it most. Food suppliers (restaurants, schools, hotels, hospitals, and grocery stores) and food banks can go to our website, create a profile, and then schedule deliveries and pickups for extra food. Our goal with this application is to make the process of donating and receiving extra food as seamless as possible. Once food suppliers and food banks provide information such as the food they have, the food they need, and when they are open to donate and receive food, our app takes care of the rest. We developed an advanced algorithm to determine the most efficient routes for drivers to pick up food from food suppliers, and deliver them to food banks. The drivers for our platform are crowd sourced volunteers similar to Uber and Lyft. The driver is presented with the route they need to drive, and the food suppliers and food banks do not have to expel any additional effort.
How We built it
The graph algorithm approximates the Traveling Salesman algorithm. It separates different nodes of the graph into source and sink elements, estimates an ideal drop off for each food shelter, and then uses a preorder traversal of a minimum spanning tree to create the truck route. It's written in c++ with the Boost Graph api. We use JSON to define our data the algorithm runs on, and write another JSON file to be read and displayed in the website.
What We learned
Our team learned that coming across annoying challenges and bugs are typical to the development process. We expanded our experience with full-stack development. In addition to this, we heavily researched global food waste, and the amount of food wasted, and people in need is devastating. Completing this project really opened our team's eyes into this problem and we are all more conscious about thew amount of food we eat and are more grateful for what we have.
What's next for Consume - Food Waste Solution
Our team wants to improve Consume to work on mobile devices so that it is more accessible and easier to use for more people.
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